AI Voice Receptionist Development -- 2

@Julian29

Hello, I read your requirements carefully and understood very well about the project scope and can start working accordingly in stages. I have 10+ years of experience in AI, NLP, and full-stack development, including building voice-enabled assistants and chatbots using Whisper, Dialogflow, Azure Cognitive Services, Amazon Polly, and similar tools. I can implement accurate speech-to-text, intent classification, text-to-speech response, and fallback handling, wrapped in a lightweight module ready for website integration and later expansion to Twilio/SIP. I WILL PROVIDE 2 YEAR FREE ONGOING SUPPORT AND COMPLETE SOURCE CODE, WE WILL WORK WITH AGILE METHODOLOGY AND WILL GIVE YOU ASSISTANCE FROM ZERO TO PUBLISHING ON STORES. Deliverables will include a testable Chrome demo page, proper handling of expected and fallback queries, transcript logging, and full setup instructions. Code will be clean, well-commented, and easily maintainable. I eagerly await your positive response. Thanks.

@ZohaibRoy

⭐⭐⭐⭐⭐ Create a Voice-Driven Receptionist for Your Business ❇️ Hi My Friend, I hope you're doing well. I reviewed your project requirements and see you are looking for a voice-driven receptionist solution. Look no further; Zohaib is here to help you! My team has successfully completed 50+ similar projects, focusing on voice recognition and natural language processing. I will create a full-stack solution that includes speech-to-text, intent handling, and audio playback, all wrapped in a module for easy integration. ➡️ Why Me? I can easily create your voice receptionist system as I have 5 years of experience in voice technology, natural language processing, and web integration. My expertise includes speech recognition, intent classification, and text-to-speech. I also have a strong grip on tools like Dialogflow, Azure Cognitive Services, and Twilio for seamless communication. ➡️ Let's have a quick chat to discuss your project details. I can share samples of my previous work, demonstrating my capability in this area. Looking forward to chatting with you! ➡️ Skills & Experience: ✅ Speech Recognition ✅ Natural Language Processing ✅ Text-to-Speech ✅ Intent Classification ✅ Audio Playback ✅ REST API Integration ✅ Twilio Integration ✅ Python Programming ✅ Node.js Development ✅ System Logging ✅ User Experience Design ✅ Setup Documentation Waiting for your response! Best Regards, Zohaib

@OutsourceMan

⭐⭐⭐⭐⭐ We at CnELIndia, alongside Raman Ladhani, can deliver a fully integrated voice-driven receptionist tailored to your requirements. We will implement accurate English STT using Whisper or Azure Cognitive Services, combined with robust NLP for intent recognition to handle business-hour and location queries. Text-to-speech will use Amazon Polly or Azure TTS for friendly, natural responses. For fallback, the system will politely request clarification and log all transcripts. We will wrap this as a drop-in module with a REST webhook for immediate website integration and future Twilio/SIP expansion. Our approach includes a Chrome demo page, complete source code in Python/Node, and clear setup instructions. With prior experience in Dialogflow, Whisper, and cloud TTS, we can deliver a working prototype in 2–3 weeks, ensuring scalable and maintainable deployment.

@kareemmaize

Hi there For this AI voice receptionist, the key is designing a low-latency speech pipeline that feels conversational rather than mechanical. I would structure the system as follows: Speech-to-Text: OpenAI Whisper API or Azure Speech for accurate English transcription. Intent Handling: Lightweight intent classifier (rule-based + embeddings) to detect hours, closing time, and location. This keeps responses deterministic for business-critical queries. Text-to-Speech: Azure Neural TTS or Amazon Polly for natural, human-like voice output. Fallback Logic: Confidence scoring on intent classification — if below threshold, trigger clarification prompt and log transcript for future training. The system would expose a simple REST endpoint and include a browser-based demo page where a user speaks via microphone, receives spoken reply, and sees transcript logs. The architecture will be modular so expanding to Twilio voice calls later only requires swapping the audio transport layer — the AI core remains unchanged. My approach is structured. Build STT - Intent - Response - TTS pipeline. Wrap in REST webhook + browser demo UI. Implement transcript logging and fallback confidence logic. Deliver clean, documented source code. If this aligns, let’s discuss in detail via private chat.

@usamae

Built a few AI voice systems before using Whisper/Deepgram for STT and ElevenLabs for TTS - the stack you are describing here is pretty familiar. The intent classification + fallback handling is the interesting part. For this I would use Deepgram for STT, GPT-4o function calling for intent + answers (reliable out of the box), and ElevenLabs for natural voice output. The REST webhook wrapper is a clean fit for yoru existing widget, and Twilio expansion later is just another adapter on top of the same core. Can have a working demo with all 3 acceptance critera passing in about a week. What is the website widget built on? - Usama

@rbtech1984

Hello There!!! ★★★★ ( AI Voice Receptionist Development ) ★★★★ I understand you need a voice-driven receptionist that listens to visitors, converts speech to text, identifies intent, and responds with natural, friendly audio, with a fallback system for unclear queries. The module should integrate easily into your website and be ready for future VoIP expansion. ⚜ Speech-to-text conversion for English queries ⚜ Intent recognition and response selection ⚜ Text-to-speech output with natural-sounding voice ⚜ Fallback handling for unrecognized queries ⚜ REST webhook or lightweight SDK integration ⚜ Logging and transcript management ⚜ Scalable architecture for future phone line integration With 9+ years of experience in AI voice apps and NLP, I’ve built Python and Node.js modules using Whisper, Dialogflow, and Polly to handle real-time speech interactions. I’ll ensure smooth Chrome demo functionality, clear setup, and maintainable source code. Looking forward to helping you launch a smart, human-like AI receptionist efficiently. Warm Regards, Farhin B.

@TechizeBuilder

Hi, I came across your project "AI Voice Receptionist Development -- 2" and I'm confident I can help you with it. About Me: I'm a agency owner with over 8+ years of experience in Node.js, Android, REST API. , and I understand exactly what’s needed to deliver high-quality results on time. Why Choose Me? - ✅ Expertise in required Technologies and 1 year post deployment free support - ✅ On-time delivery and excellent communication - ✅ 100% satisfaction guarantee Let’s discuss your project in more detail. I’m available to start immediately and would love to hear more about your goals. Looking forward to working with you! Best regards, Deepak

@vasudharao9

Hi, I’m a Computer Science graduate from UC Berkeley with a specialization in Artificial Intelligence. I have more than 10 years of experience working in the AI/ML space. I can help you with this project. Message me to discuss this further.

@GameOfWords

AI Voice Receptionist Development I’m a full-stack software engineer with expertise in React, Node.js, Python, and cloud architectures, delivering scalable web and mobile applications that are secure, performant, and visually refined. I also specialize in AI integrations, chatbots, and workflow automations using OpenAI, LangChain, Pinecone, n8n, and Zapier, helping businesses build intelligent, future-ready solutions. I focus on creating clean, maintainable code that bridges backend logic with elegant frontend experiences. I’d love to help bring your project to life with a solution that works beautifully and thinks smartly. To review my samples and achievements, please visit:https://www.freelancer.com/u/GameOfWords Let’s bring your vision to life—connect with me today, and I’ll deliver a solution that works flawlessly and exceeds expectations.

@webmasters486

Hi there, I’ve reviewed your project and understand you need a voice-driven receptionist that listens, understands, and responds naturally to visitor or caller queries. I can build a full-stack solution with speech-to-text, intent classification, text-to-speech, and audio playback, delivered as a lightweight module ready to integrate into your existing website widget, with future expansion to Twilio or SIP/VoIP. The system will accurately handle your key queries (“What time do you open?”, “When do you close?”, “Where are you located?”) and politely request clarification for unrelated questions, logging all transcripts for review. I can implement this using Python or Node with Whisper or Dialogflow for STT/NLP and Amazon Polly or Azure Cognitive Services for TTS, wrapped behind a simple REST webhook or SDK. The deliverable will include a demo page for Chrome testing, fully documented setup instructions, and clean, maintainable source code. I focus on reliable, human-like interactions and can start immediately, providing a concise plan and timeline for deployment. Best regards, Muhammad Adil Portfolio: https://www.freelancer.com/u/webmasters486

@kishanbwts

I can build your voice receptionist module with clear speech-to-text, intent classification, and natural text-to-speech responses, plus smart fallback handling. In a past project, I created a similar voice assistant using Whisper for transcription and Dialogflow for intent recognition, which handled common FAQs and logged unclear requests for review. My plan is to build a simple REST webhook wrapped in Node.js that connects the components seamlessly. For speech recognition, I suggest Whisper for accuracy, paired with intent classification using a lightweight NLP model trained on your FAQs. Amazon Polly or Azure TTS will provide the natural voice responses. I will create a demo page where you can test the flow in Chrome, so you can speak and hear replies instantly. For fallback, the system will politely ask for clarification and log the transcript for future tuning. Two quick checks: - How specific do you want the intent categories at this stage—just location and hours, or room to expand? - Any preference for cloud providers or keeping things open source? I can deliver a working module and clear instructions within a week. Ready to get this kicked off as soon as you decide.

@sarbtech123

As an experienced Python developer with a focus on backend development, I can offer you the expertise you need to successfully build your voice-driven receptionist. Having already worked on live production systems, I guarantee you results that are stable, long-term maintainable and easy to scale. In regards to this specific project, I have comprehensive knowledge in Python and other mainstream languages which would give you flexible options for development. My skills in using frameworks like Django, FastAPI and Flask, will ensure accelerated application setup with clean architecture. Further, my understanding of automation coupled with Zapier and API workflows will provide efficient task responses, an invaluable asset when developing a voice receptionist system. My commitment to clear communication and efficient delivery without shortcuts or fragile hacks ensures timely reporting of project updates and realistic timelines. By working together, we can replace manual work processes, automate operations, and build scalable systems that will add significant value to your business operations. Let's discuss your project in detail and get started on building the optimal solution together.

@sumanm596

Hi, thanks for sharing the project details. Yes, this is something our team can help you build. We have experience working with conversational AI systems using technologies like Whisper, Dialogflow, Azure Speech, and Amazon Polly. Our approach would be to create a modular voice assistant that handles speech recognition, intent detection, and natural voice responses, while keeping the integration simple through a REST webhook so it can easily plug into your existing website widget and later extend to Twilio for phone calls. We can first deliver a browser-based demo where users speak through Chrome and receive voice responses for queries like business hours or location, along with fallback clarification when the system is unsure. Logging and clear setup documentation will also be included. If you'd like, I can share a short technical plan and estimated timeline for implementation. Best regards, Suman Mallik

@proy89

Hi, I can build a simple voice receptionist that listens to a visitor, understands the question, and replies with a natural voice. It will work in a browser now and can later connect to a phone line through Twilio. How I’ll do it: 1. Create a small backend service (Node.js or Python). 2. Make a simple demo page with a microphone button that records the user’s voice in Chrome. 3. Send the recorded audio to the backend. 4. Convert speech to text using a reliable service like Whisper or Azure Speech. 5. Check the text to detect the intent (open hours, closing hours, location). 6. Return the correct response from a small configuration file. 7. If the question doesn’t match anything, reply with “Sorry, could you tell me a bit more about that?” and log the transcript. 8. Convert the response text into natural audio using Amazon Polly or similar. 9. Send the audio back to the browser so the page plays the reply. 10. Expose the system through simple REST endpoints so it can later connect to Twilio or another VoIP service. You’ll receive the source code, setup steps, and a demo page where you can speak and hear the reply immediately. The design will stay simple so you can easily expand it with more questions later. Thanks

@xoheruox

Hello, Now Meta is a company with a decade of expertise in Matching Job Skills. I have carefully reviewed the requirements for the AI Voice Receptionist Development project. Our team will follow a structured process including accurate speech-to-text recognition, intent classification, natural-sounding text-to-speech responses, and polite fallback prompts. We plan to integrate the solution seamlessly into your existing website widget with the potential for expansion to a phone line using Twilio or similar services. I invite you to open a chat for a more personalized discussion to further understand your needs and how we can tailor our approach to meet your project requirements effectively. Regards, Now Meta

@MIndlabsAi6

Hello, I am Vishal Maharaj, with 20 years of experience in Python, REST API, Android, and Node.js. I have carefully reviewed the requirements for the AI Voice Receptionist Development project. I propose to implement accurate speech-to-text recognition, NLP for intent classification, natural-sounding text-to-speech responses, and a user-friendly fallback system. The solution will be integrated seamlessly into your existing website widget and easily scalable to a phone line using Twilio or similar services through a REST webhook or lightweight SDK. I will ensure a demo page for testing, correct responses for specific inquiries, handling of unrelated questions, and provide clear setup instructions along with the source code in Python, Node.js, or a comparable language. Let's discuss further details in the chat. Cheers, Vishal Maharaj

@dataspro

Nice to meet you , It is a pleasure to communicate with you. My name is Anthony Muñoz, I am the lead engineer for DSPro IT agency and I would like to offer you my professional services. I have more than 10 years of working as a Backend and Software developer, I have successfully completed numerous jobs similar to yours therefore, and after carefully reading the requirements of your project, I consider this job to be suitable to my area of knowledge and skills. I would love to work together to make this project a reality. I greatly appreciate the time provided and I remain pending for any questions or comments. Feel free to contact me. Greetings

@Cmonosoft

Hi there, I can help you build the voice-driven receptionist with a clean, modular architecture that works on the web today and can later connect to a phone line through services such as Twilio. Implementation Process - Speech to text will use a reliable engine such as OpenAI Whisper or Azure Cognitive Services Speech to ensure accurate English transcription. The recognized text will be passed to an intent classification layer built with a lightweight NLP model or rule-based intent mapping for business hours and location queries. For response generation, the system will retrieve the correct answer from a structured configuration file or small knowledge base. If the intent confidence is low or the request does not match a supported topic, the system will trigger a polite clarification message and log the transcript for review. Text to speech will be generated using natural voice synthesis such as Amazon Polly or a similar service to deliver friendly, human-like responses. I can start immediately and provide a working prototype within a few days after confirming your preferred toolchain. Thanks Saurabh

@Shaiwan

❗❕‼️⁉️ Hello ⁉️‼️❕❗ ❗❕❗❕❗❕ I understand you need an AI voice receptionist that converts speech to text, classifies intent, and responds naturally while handling unclear queries gracefully. I HAVE SOME QUESTIONS REGARDING THE PROJECT SEND ME A MESSAGE FOR MORE DISCUSSION ❗❕❗❕❗❕ ⇆ ⇆ ⇆ I will develop a full-stack module with accurate English STT, NLP-based intent recognition, TTS for human-like responses, a polite fallback system for unclear queries, and a REST webhook/SDK integration for website or future Twilio/VoIP expansion ⇆ ⇆ ⇆ With 7+ years of experience in Python, Node.js, NLP, and audio service integrations, I deliver robust, scalable, and user-friendly AI solutions. My approach: design the STT and TTS pipeline, implement intent classification and response logic, integrate with a demo page, test all scenarios, and deliver source code with clear setup instructions. Let’s chat to clarify your preferred tools and timeline. Best Regards, Shaiwan Sheikh